Rural Developing Level Clustering Based on KMEANS From Electricity Perspective

Abstract

KMEANS cluster analysis is widely used in big data environments. Due to the electricity consumption is closely related to the industrial development and living conditions of rural industry production and residents, and it is forming the electricity big data environment, it has given a perspective to analyze the rural developing level from big data mining technology such as KMEANS clustering method. The study of rural developing is becoming an important issue at present. In this paper, we use KMEANS clustering the rural developing levels, and we identify 4 main factors from 14 factors at four aspects: prosperous industry, eco-friendly living, affluent living and agricultural development, and from the case study, 5 types of rural developing level are clustered by KMEANS technology. The case study is also proving the proposed method are effectiveness for rural developing level analysis in the current big data situation.